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import gradio as gr
import pandas as pd
from src.about import (
CITATION_BUTTON_LABEL,
CITATION_BUTTON_TEXT,
EVALUATION_QUEUE_TEXT,
INTRODUCTION_TEXT,
LLM_BENCHMARKS_TEXT,
TITLE,
)
# Simplified DataFrame for the leaderboard
data = {
"Model": [
"Handwritten TAG",
"Zero-shot Text2SQL",
"Zero-shot Text2SQL + LM Generation",
"RAG (E5)",
"RAG (E5) + LM Rerank"
],
"Code": [
"", # Handwritten TAG doesn't have a code link
"", # Zero-shot Text2SQL doesn't have a code link
"", # Zero-shot Text2SQL + LM Generation doesn't have a code link
"", # RAG (E5) doesn't have a code link
"" # RAG (E5) + LM Rerank doesn't have a code link
],
"Execution Accuracy": [
"55%", # Handwritten TAG
"17%", # Zero-shot Text2SQL
"13%", # Zero-shot Text2SQL + LM Generation
"0%", # RAG (E5)
"2%" # RAG (E5) + LM Rerank
]
}
leaderboard_df = pd.DataFrame(data)
# Simplified Gradio app
with gr.Blocks() as demo:
gr.HTML(TITLE)
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
with gr.Tabs(elem_classes="tab-buttons") as tabs:
with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
# Highlight the top row in green for "Handwritten TAG"
with gr.Row():
gr.Dataframe(
value=leaderboard_df,
headers=["Model", "Code", "Execution Accuracy"],
datatype=["str", "str", "str"],
row_count=(5, "dynamic"),
wrap=True,
elem_id="leaderboard",
type="pandas"
)
with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
with gr.TabItem("🚀 Submission Instructions ", elem_id="llm-benchmark-tab-table", id=3):
gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
demo.launch()
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